The contents of all patents, patent applications, published articles, books, reference manuals and abstracts cited hereinbelow are herein incorporated by reference in their entirety to more fully describe the state of the art to which the invention pertains.
Essential for the appropriate and optimal treatment and handling of patients who present with suspected myocardial infarction is an early diagnosis within the first hours after the onset of symptoms, e.g., chest pain, that are believed to be of cardiac origin. Although the 12-lead electrocardiogram (ECG) is usually immediately available, it is nondiagnostic on admission for the vast majority (e.g., up to about 60%) of patients. In cases with typical ST-segment elevations, the diagnosis of acute myocardial infarction (AMI) is straightforward. However, in those patients with a non-diagnostic ECG, a diagnosis according to World Health Organization (WHO) criteria can only be made by also considering the results of biochemical marker tests.
There has been interest in new biochemical markers for an early rule-in and rule-out of AMI. The diagnostic sensitivity and specificity of such markers may be high; however, they are often not sensitive enough for confirming or ruling out AMI immediately upon admission. It is a goal in the art to be able to identify at an early stage those patients, among the heterogeneous group of patients with chest pain, who have actually suffered an AMI, for hospital admission and early treatment, while ruling out the possibility of AMI in patients with non-AMI related chest pain to have them appropriately treated and discharged early from the emergency room.
To achieve some of the goals in the art, several methods have been proposed, such as diagnostic algorithms based on clinical data (T. H. Lee et al., 1991, N. Eng. J. Med., 324:1239-1246; J. Jonsbu et al., 1993, Eur. Heart J., 14:441-446) or biochemical markers (P. O. Collinson et al., 1988, Ann. Clin. Biochem., 25:376-382; B. Lindahl et al., 1995, Coron. Artery Dis., 6:321-328). In addition, artificial neural networks, based on clinical data including ECG (W. G. Baxt, 1991, Ann. Intern. Med., 115:843-848; W. G. Baxt, 1992, Ann. Emerg. Med., 21:1439-1444), biochemical markers (J. W. Furlong et al., 1991, Am. J. Clin. Pathol., 96:134-141; S. Pedersen et al., 1996, Clin. Chem., 42:613-617) and frequent sampling and measurement of selected markers of AMI (J. Ellenius et al., 1997, Clin. Chem., 43:1919-1925) have been used as an alternative technique in AMI diagnosis.
Reflex algorithms (i.e., algorithms which specify selection of subsequent tests based on results of previous tests, without the need for subjective human decision-making in selecting tests) have been employed in the areas of clinical chemistry and laboratory medicine for more than a decade. Initially, such algorithms were suggested for the assessment of thyroid disease, where an assay for thyroid stimulating hormone (TSH) was the first-line test, and further markers were chosen, or omitted, on the basis of the TSH result (J. Klee, 1987, J. Clin. Endocrinol., 64:641-671). To date, thyroid testing is the only area in laboratory medicine in which reflex testing has found acceptance among practitioners in the art. Reflex algorithms for the detection of other disease states and medical conditions are not conventionally employed. Thus, reflex testing and the use of algorithms for the diagnosis of other diseases are needed in the art and promise to improve the diagnostic process through their efficiency, effectiveness and reduction of costs of further unwarranted testing.
An abstract by T. E. Caragher et al. (1997, Clin. Chem., 43:S108) discloses serial measurements of several AMI markers at defined time points. The criteria for confirmation of AMI were defined based on the results of the testing algorithm. The algorithm of Caragher et al. is not a reflex algorithm, because subsequently ordered tests do not depend on the previous results obtained.
J. Ellenius et al. disclosed a computer assisted approach to diagnose acute myocardial infarctions. In this report, creatine kinase isoforms, myoglobin and Troponin T were measured in short time intervals and the diagnosis was made by processing the results using a neural network. Such a neural network is not performed in the manner of reflex testing and does not try to minimize the number of necessary tests. Instead, it focuses on obtaining the most accurate information as early as possible from several different tests run in very short intervals.
It is appreciated, therefore, that there is a need for further improvements and developments in detecting myocardial infarction, and more particularly, for a reflex method for specific and sensitive detection of AMI.